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aiops_study

智能运维是一项系统工程,算法只是其中一个环节,好的算法还需要高效的平台去支持投产和应用。
本文主要整理aiops领域相关的方法,并进行持续学习。

本页面的编写,学习参考markdown语法

异常检测

根因分析

故障预测

事件预测

时序预测

告警事件

告警收敛

  1. 【2023IEEE】Dynamic Graph Neural Networks-based Alert Link Prediction for Online Service Systems
    • 首先构建某个时刻的告警快照图,里面包含了告警、指标、以及初步得到的一些链接关系。这些关系包括指标相似关系、指标触发告警的关系。基于多个连续快照图,可以建模得到告警的时空表示,此所谓动态图神经网络建模。图中还结合了告警嵌入(语义信息)、指标嵌入(时序信息)的方法。最终为了预测告警之间的链接,还需要打标数据集,这是一大门槛。但也因为是有监督学习,可以实现端到端训练,充分利用深度学习的表达能力。最后有源码开放,值得点个赞。

事件分类

告警优先级排序

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